What are hierarchical clustering algorithms?

What are hierarchical clustering algorithms?

Hierarchical clustering algorithms are methods of cluster analysis that build a hierarchy of clusters. They can be divided into two types: agglomerative (bottom-up) and divisive (top-down).

How does agglomerative clustering work?

Agglomerative clustering starts with each data point as its own cluster and iteratively merges the closest pairs of clusters until only one cluster remains or a specified number of clusters is achieved.

What are some applications of hierarchical clustering?

Hierarchical clustering is used in various fields such as biology for phylogenetic analysis, marketing for customer segmentation, and image analysis for organizing similar images.

Can you explain the difference between single-linkage and complete-linkage clustering?

Single-linkage clustering merges clusters based on the shortest distance between points in different clusters, while complete-linkage clustering merges based on the longest distance.